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and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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PhD process MATH+ Fridays – Kovalevskaya Colloquium Each semester, MATH+ designates one of the MATH+ Friday colloquia as the Sonia Kovalevskaya Colloquium . This lecture features female mathematicians
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hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research
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medical image data. Vivid Interest in interdisciplinary research, closely working together with pathologists, medical experts, computer scientists and other researchers. Independent and pro-active work
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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processes in inflammatory contexts Planning and carrying out own independent research projects Planning and independent execution of experiments Independent data processing and evaluation Supervision
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18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
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Chair of Biological Imaging 11.07.2023, Wissenschaftliches Personal We now seek a highly qualified and motivated PhD student (f/m/d) to design, develop, and test novel optoacoustic sensing platforms
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes